Assessment of the Levels of Airborne Bacteria, Gram-Negative Bacteria, and Fungi in Hospital Lobbies.

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by  Park, Dong-Uk

Int. J. Environ. Res. Public Health 2013, 10, 541-555; doi:10.3390/ijerph10020541
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International Journal of
Environmental Research and
Public Health
ISSN 1660-4601
www.mdpi.com/journal/ijerph
Article
Assessment of the Levels of Airborne Bacteria, Gram-Negative
Bacteria, and Fungi in Hospital Lobbies
Dong-Uk Park 1,*, Jeong-Kwan Yeom 2,3, Won Jae Lee 3 and Kyeong-Min Lee 1,4
1 Department of Environmental Health, Korea National Open University, Seoul, 110-791, Korea
2 Hanbul Energy Manufacturing, Sampyeong-Dong, Bundang-Gu, Gyeonggido, 463-413, Korea
3 Department of Global Healthcare Management, Gachon University, Gyeonggido, 461-701, Korea
4 Institute for Occupational Health & Graduate School of Public Health, Yonsei University, Seoul,
120-752, Korea
* Author to whom correspondence should be addressed; E-Mail: [email protected];
Tel.: [phone]; Fax: [phone].
Received: 31 October 2012; in revised form: 4 January 2013 / Accepted: 16 January 2013 /
Published: 31 January 2013

Abstract: Aims: We assessed the levels of airborne bacteria, Gram-negative bacteria
(GNB), and fungi in six hospital lobbies, and investigated the environmental and hospital
characteristics that affected the airborne microorganism levels. Methods: An Andersen
single-stage sampler equipped with appropriate nutrition plate agar was used to collect the
samples. The three types of microorganisms were repeatedly collected at a fixed location in
each hospital (assumed to be representative of the entire hospital lobby) from 08:00 through
24:00, with a sampling time of less than 5 min. Temperature and relative humidity were
simultaneously monitored. Results: Multiple regression analysis was used to identify the
major factors affecting microorganism levels. The average levels of bacteria
(7.2 × 102 CFU/m3), GNB (1.7 × 10 CFU/m3), and fungi (7.7 × 10 CFU/m3) indicated that all
hospital lobbies were generally contaminated. Season was the only factor that significantly
affected the levels of all microorganisms (p < 0.0001), where contamination was the highest
during the summer, significantly higher than during the winter. Other significant factors
varied by microorganism, as follows: airborne bacteria (number of people in the lobby,
sampling time), GNB (scale of hospital), and fungi (humidity and air temperature).
Conclusions: Hospital lobby air was generally contaminated with microorganisms,
including bacteria, GNB, and fungi. Environmental factors that may significantly influence
the airborne concentrations of these agents should be managed to minimize airborne levels.
Int. J. Environ. Res. Public Health 2013, 10 542

Keywords: hospital lobby; bacteria; fungi; Gram-negative bacteria (GNB)

1. Introduction
Exposure to biological agents (including microorganisms) is associated with a wide range of major
public health issues, such as infectious diseases, acute toxic effects and allergies [1]. Although
airborne microorganisms encountered in hospital lobbies are apparently harmless to healthy people,
they can cause adverse health effects in immune-compromised people. Many of those who pass
through hospital lobbies belong to the vulnerable group of weak, elderly, and infirm people, and thus
may be very sensitive to biological hazards. In particular, hospitalized patients could be at significantly
increased risk of bio-aerosol exposure [2].
Airborne microorganisms originate not only from people (including patients), but are also spawned
by various indoor hospital characteristics and outdoor environmental sources. There are a number of
such factors that may be related to the generation of bio-aerosols in the lobby of a hospital. Airborne
microorganisms and other sources of contamination in hospitals must be reduced to a minimum, because
many of the people passing through hospital lobbies could be very sensitive to these hazardous agents.
Thus, to maintain the lowest possible airborne microorganism levels in hospital lobbies, it is crucial to
identify the factors influencing these levels. Hospital buildings may be regarded as dynamic
environments affected by season, weather conditions, indoor ventilation system design and operation,
intrusion of moisture, the outdoor microbial load and the number of occupants and visitors, and human
activities. These factors can be related to a condition for microbial growth. Nutrient availability, indoor
temperature, and shelter generally cannot be managed to limit indoor microbial survival and growth.
Several studies have been conducted to determine the factors influencing microbial growth in hospital
environments. Scaltriti et al. reported that risk factors for microbial contamination of air in operating
theatres were the frequency of door-opening, taken as an index of staff and visitor movement, was a
positive predictor of raised bacterial counts [3]. Obbard et al. identified the occupant density as the key
factor influencing the level of airborne bacteria. Humidity was also found to be important factor
depending on the particular location within the hospital [4].
To date, airborne microorganism levels have been reported in hospital clean rooms, such as operating
rooms, hospital rooms, intensive care units, surgical units, hematological wards, and maternity
wards [5–7]. To the best of our knowledge, no previous studies have investigated how hospital
characteristics are associated with airborne levels of microorganisms in lobbies. Accordingly, we
examined the levels of airborne bacteria, gram negative bacteria (GNB), and fungi with respect to
environmental and other characteristics in the lobbies of six hospitals.
2. Methods
2.1. Monitoring Strategy
Microorganism levels, relative humidity, and temperature were measured in six Korean hospitals
with more than 500 beds, between July (summer) and January (winter). General characteristics for
general hospital lobby were shown in Table 1. We are unaware of any hospital that has installed carpet
Int. J. Environ. Res. Public Health 2013, 10 543

on the entire hospital floor (including the lobby) in Korea. No hospitals have a wooden construction or
use other materials that would provide a good environment for microbial growth. A different hospital
was examined every month. Air samples were repeatedly taken from the start of lobby service
(08:00 AM) through the end of lobby service (18:00 PM), continuing until midnight (24:00). The air was
monitored after lobby service hours for comparison with samples taken during lobby service hours.
Sampling instruments were placed at a height of around 1.2–1.5 m, in a fixed location assumed to be
representative of the entire lobby.
Table 1. General characteristics for the hospitals investigated
Hospital No of bed Building age, year Area of lobby (m2)
A 710 23 2,764
B 1,000 10 2,717
C 1,200 3 2,413
D 530 26 1,674
E 867 19 2,712
F 800 13 1,710
Our microbial sampling strategy was designed to best represent the level of microorganisms
generated in hospital lobby environment. An Anderson single-stage cascade sampler was used for all
collections, with a flow rate of 28.3 L/min and a sampling time of less than 5 min to avoid the
collection of unaccountable microorganisms. The airborne microorganisms were targeted one after
another, using a 20 mL nutrient plate (tryptic soy agar, TSA) for bacteria, MacConkey agar (MAC) for
GNB, and sabouraud dextroseagar with chloramphenicol (SDAC) for fungi) coupled inside the stage
sampler. When changing the collection plates, the stage hole was sterilized with a 70% ethanol
solution to prevent cross-contamination. To evaluate the representative level of airborne microorganisms
during the morning (08:00–13:00), afternoon (13:00–18:00) and after lobby service (18:00–24:00), three
or four samples by type of microorganism were those taken in each respective period. The sampling
interval between types of microorganisms was the duration required to both change the collection plates
and take samples for the other two types of microorganisms. After sample collection, the agar plates
were transported to the laboratory and incubated at 37 ± 1 °C for 2 days for bacteria and GNB and at
25 ± 1 °C for 4 days for fungi [8]. Specific statistical corrections were made using correction factors
obtained for each growing medium from Conversion Tables provided by single stage operating
manual [9]. For all the media the minimum detectable number of colony forming units (CFU) was 30
per sample. Data below minimum detectable number was treated as missing. The microbial counts were
expressed in terms of colony-forming units (CFU) per unit volume of air (m3). Total culturable
bacterial and fungal counts were compared to ambient environmental levels (background) to determine
the degree of incremental levels generated during household waste handling. Our microbial sampling
strategy mentioned above was determined to best represent the level of microorganisms generated in
hospital lobby. Direct-reading instruments for monitoring the temperature and humidity (IAQ, Model;
8762, TSI, Shoreview, MN, USA) were placed next to the cascade sampler to simultaneously monitor
air temperature and humidity during each sampling interval.
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2.2. Data Analysis
The data-logging interval was set at 30 s, averaged with a time-weighted average. Direct-reading
temperature, humidity, and CO results were matched with airborne microorganism levels measured
2
during the sampling period of microorganisms. We selected a number of environmental variables and
hospital characteristics that may influence airborne microorganism levels in hospital lobbies. The
quantitative variables were categorized based on subjective classification, as follows: the scale of a
hospital expressed by the number of beds (<1,000 vs. ≥1,000), lobby age (<10 years, 10–19 years, and
≥20 years), the input location of outdoor air in the HVAC (Heating, Ventilating and air conditioning)
system (underground vs. ≥1st floor), the number of filters in the HVAC system (pre and medium vs.
only medium), and lobby volume (<10,000 m3 vs. ≥10,000 m3). Both lobby service time and cleaning
time were dichotomized into “on (08:00–18:00)” and “off (18:00–24:00)”. Correlations between the
selected independent variables were evaluated to identify potential problems prior to offering to the
multiple regression model. Correlations involving at least one continuous variable were tested using
Spearman’s rho, and between two dichotomous variables using Kendall’s tau. The absolute values of all
correlation coefficients were less than 0.5, so all of the above variables were considered appropriate for
input to a single model.
Simple linear regression analysis was used to examine the relationships among quantitative variables
such as air temperature, humidity, CO level, and the number of people in the lobby during sampling,
2
and microbial concentrations. Analysis of variance (ANOVA) was employed to compare mean
microorganism levels between categories of qualitative variables. Only variables with p-values less
than 0.25 were ultimately included in the multiple regression analysis [10]. Stepwise analysis was used
to identify the final factors that significantly affected the airborne concentrations of microorganisms.
Descriptive statistics were obtained and data analysis was conducted using the STATA (Version 11.0)
software (Stata Corp. LP, College Station, TX, USA).
The concentrations of all microorganisms were found to be distributed log-normally. To improve
the statistical models used in this study, the microorganism data employed as dependent variables were
all log-transformed. One of the categories served as a reference group for comparison with the other
groups. Each descriptive factor was given a value of zero when used as a reference variable.
3. Results
Temperature, relative humidity and carbon dioxide level (CO ) was shown by hospital in Table 2.
2
The mean level of airborne bacteria (7.2 × 102 CFU/m3) was lower than the indoor air quality standard
(8.0 × 102 CFU/m3) enforced by the Korean Environmental Protection Agency [11], while 30% of the 76
samples exceeded the standard. The average concentration of GNB was 1.7 × 10 CFU/m3, although 12
samples were below the limit of detection. The airborne fungi level ranged from 1.1 to 2.2 × 102
CFU/m3. Significant differences were found among the six hospitals (p < 0.0001; Table 3).
Int. J. Environ. Res. Public Health 2013, 10 545

Table 2. Temperature, relative humidity and carbon dioxide level (CO ) by hospital.
2
Temperature, °C Relative Humidity, % CO , ppm
2
No. of
Hospital Range Range Range
Samples * Mean ± SD Mean ± SD Mean ± SD
(min–max) (min–max) (min–max)
A 13 25.1 ± 0.4 24.5–25.9 66.8 ± 3.9 62.2–72.6 801 ± 221 458–1,061
B 12 26.5 ± 0.1 26.3–26.6 70.6 ± 1.7 67.6–72.8 432 ± 44 377–509
C 12 25.9 ± 0.4 25.1–66.3 65.7 ± 0.1 65.6–65.8 503 ± 87 393–625
D 12 25.8 ± 0.9 24.0–26.9 65.3 ± 0.7 63.5–65.8 481 ± 109 342–651
E 13 22.9 ± 0.8 21.7–24.1 65.8 ± 0.1 65.6–66.0 558 ± 111 366–692
F 14 20.7 ± 1.2 17.4–21.8 65.0 ± 0.4 64.4–65.6 409 ± 50 345–486
Total 76 24.4 ± 2.2 17.4–26.9 66.5 ± 2.5 62.2–72.8 531 ± 176 342–1,061
No of sample: number of time-weighted average (TWA) of data logged every 30 s during the sampling period of microorganisms.
Table 3. Airborne microorganism levels by hospital.
Bacteria, CFU/m3 GNB, CFU/m3 Fungi, CFU/m3
No of
Hospital Range Range Range
sample GM GSD GM GSD GM GSD
(min-max) (min-max) (min-max)
A 13 8.7 × 102 1.6 3.8 × 102 – 1.8 × 103 10 2.7 4 – 1.1 × 102 53 1.9 21 – 2.1 × 102
B 12 6.2 × 102 3.2 50 – 2.3 × 103 21 2.1 5 – 5.6 × 10 79 1.8 29 – 2.0 × 102
C 12 7.6 × 102 1.8 2.8 × 102 – 1.8 × 103 18 1.9 7 – 5.2 × 10 66 2.1 18 – 1.5 × 102
D 12 6.8 × 102 1.7 3.3 × 102 – 1.8 × 103 11 2.3 4 – 4.7 × 10 83 2.1 18 – 2.2 × 102
E 13 5.4 × 102 1.6 2.7 × 102 – 1.7 × 103 16 2.1 LOD – 4.0 × 10 59 1.9 25 – 2.1 × 102
F 14 2.0 × 102 1.7 80 – 4.5 × 102 5 1.5 LOD – 1.1 × 10 36 2.7 11 – 1.5 × 102
Total 76 5.5 × 102 2.3 5.0 × 10 – 2.3 × 103 13 2.4 LOD – 1.1 × 102 59 2.2 11 – 2.2 × 102
GM = geometric mean; GSD = geometric standard deviation, unitless; GNB = Gram-negative bacteria; LOD = Limit of detection (30 CFU/sample).
Int. J. Environ. Res. Public Health 2013, 10 546

Our results indicate that the lobby air in all six hospitals was generally contaminated to some extent.
We observed a clear pattern in microorganism levels over time, from the start of lobby service (08:00) to
the end of lobby service, and after hours until midnight (Figure 1).
Figure 1. Daily variation in airborne microorganism concentrations (mean and range
measured at six hospitals during summer, fall, and winter).
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The airborne bacteria level was higher during lobby service hours (between 08:00 and 18:00), when
crowds of people were present and during summer (Figure 2).
Figure 2. Variation in airborne microorganism concentrations by season.
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Table 4. Relationship between the levels of log-transformed airborne microorganism and quantitative variables.
Airborne microorganism Relative humidity, % Temperature, °C Number of people present CO , ppm
2
level, CFU/m3 β SE Model p R2 β SE Model p R2 β SE Model p R2 β SE Model p R2
Bacteria NS NS NS 0.01 0.18 0.038 0.0001 0.23 0.01 0.001 <0.0001 0.37 0.01 0.001 <0.0001 0.37
GNB 0.05 0.04 0.2197 0.02 0.14 0.05 0.0068 0.1 NS NS NS NS NS NS NS NS
Fungi 0.09 0.034 0.0127 0.08 NS NS NS NS 0.002 0.001 0.056 0.05 0.002 0.001 0.056 0.05
GNB: Gram-negative bacteria; NS = not statistically significant at p = 0.25.
Table 5. The levels of log-transformed bacteria, gram-negative bacteria, and fungi among the categories of occupational and environmental variables.
Bacteria, CFU/m3 GNB, CFU/m3 Fungi, CFU/m3
Independent No of
ANOVA ANOVA
variables sample Mean SD Mean SD Mean SD ANOVA model p
model p model p
Sampling time
Service hours
44 9.3 × 102 5.7 × 102 P ≤ 0.0001 1.5 × 10 1.3 × 10 P = 0.0422 5.6 × 10 3.3 × 10 p < 0.0001
(08:00–18:00)
After service hours
32 4.4 × 102 3.0 × 102 2.0 × 10 2.2 × 10 1.1 × 102 6.4 × 10
(18:00–24:00)
Season
Summer 25 9.7 × 102 6.2 × 102 p = 0.0001 2.2 × 10 2.4 × 10 p = 0.0005 7.8 × 10 5.4 × 10 p = 0.0206
Fall 37 7.5 × 102 4.3 × 102 1.8 × 10 1.3 × 10 8.6 × 10 5.6 × 10
Winter 14 2.3 × 102 1.1 × 102 0.4 × 10 0.3 × 10 5.3 × 10 4.7 × 10

Scale of hospital (number of beds)
<1,000 52 6.3 × 102 4.4 × 102 p = 0.0192 1.3 × 10 1.7 × 10 p = 0.0016 7.3 × 10 5.6 × 10 p = 0.1365
≥1,000 24 9.3 × 102 6.4 × 102 2.4 × 10 1.6 × 10 8.7 × 10 5.1 × 10
Lobby age (years)
<10 24 9.3 × 102 6.4 × 102 p = 0.0001 2.4 × 10 1.6 × 10 p = 0.0059 8.7 × 10 5.1 × 10 p = 0.0788
10–19 27 4.1 × 102 3.2 × 102 1.0 × 10 1.2 × 10 6.3 × 10 5.1 × 10
≥20 25 8.7 × 102 4.4 × 102 1.7 × 10 2.2 × 10 8.4 × 10 6.0 × 10
Int. J. Environ. Res. Public Health 2013, 10 549

Table 5. Cont.
Cleaning time
Service hours
37 8.7 × 102 4.4 × 102 p = 0.0001 1.8 × 10 1.9 × 10 p = 0.4623 8.3 × 10 5.7 × 10 p = 0.2351
(08:00–18:00)
After service hours
26 5.7 × 102 6.6 × 102 1.4 × 10 1.7 × 10 7.1 × 10 5.3 × 10
(18:00–24:00)

Location of fresh air inlet
underground
52 6.8 × 102 5.6 × 102 p = 0.0446 1.6 × 10 1.9 × 10 p = 0.3524 7.0 × 10 5.2 × 10 p = 0.0902
& 1st floor
higher than
24 8.3 × 102 4.5 × 102 1.8 × 10 1.3 × 10 9.3 × 10 5.7 × 10
2nd floor

Number of filters in HVAC
medium 14 2.3 × 102 1.1 × 102 p ≤ 0.0001 0.4 × 10 0.3 × 10 p = 0.0001 5.3 × 10 4.7 × 10 p = 0.0056
pre and medium 62 8.4 × 102 5.2 × 102 2.0 × 10 1.8 × 10 8.3 × 10 5.5 × 10

Lobby volume (m3)
<10,000 52 6.3 × 102 4.4 × 102 p = 0.0957 1.3 × 10 1.7 × 10 p = 0.0016 7.3 × 10 5.6 × 10 p = 0.1365
≥10,000 24 9.3 × 102 6.4 × 102 2.4 × 10 1.6 × 10 8.7 × 10 5.1 × 10
Total 76 7.2 × 102 5.3 × 102 1.7 × 10 1.7 × 10 7.7 × 10 5.4 × 10
GNB: Gram-negative bacteria
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On the other hand, the reverse pattern was detected for fungi. Higher levels of fungi were detected after
lobby service hours, when the HVAC system was not operating. Airborne microorganism levels were
regressed against quantitative factors such as air temperature, humidity, CO levels, and the number of
2
people in the lobby during sampling (Table 4), and were compared between qualitative hospital
characteristic categories (Table 5). Simple linear regression indicated that air temperature, CO level, and
2
the number of people in the lobby during sampling accounted for 23%, 25% and 37%, respectively, of the
variation observed in the airborne bacteria level (p < 0.0001). The airborne GNB level was significantly
associated only with air temperature (p = 0.068). Air temperature, humidity, and the number of people
were found to affect the level of fungi at p < 0.25 (Table 4).
Regarding GNB, all qualitative variables except cleaning time (p = 0.4623) and location of fresh air
supply (p = 0.3524) were significant at p < 0.05. The season and the number of filters in the HVAC were
significantly associated with all three types of airborne microorganism (p ≤ 0.0001), being markedly
higher in summer than in winter. Correlation matrix analysis revealed that airborne levels of GNB and
fungi were significantly correlated with one another (Table 6).
Table 6. Correlation matrix analysis results between the log-transformed levels of airborne
bacteria, gram-negative bacteria, and fungi levels (p-value)
Bacteria GNB Fungi
Bacteria 1
GNB NS 1
Fungi NS 0.43 (p = 0.0002) 1
GNB: Gram-negative bacteria; NS = not statistically
significant at p = 0.05.
All hospital and environmental variables identified as significant at p < 0.025 in the univariate
analysis were included in the multiple regression analysis (Table 7). Season was the only factor that
appeared to significantly affect airborne levels of all microorganisms. The other factors varied according
to the type of microorganism. Significant statistical models were developed to predict airborne levels of
bacteria, GNB and fungi accounting for 75% (p < 0.0001), 24% (p < 0.0001) and 36% (p < 0.0001) of
the observed variation, respectively.
4. Discussion
Most hospital-based airborne microorganism studies have been performed in clean rooms or
departments, where the risk of infection is greatest [5–7]. Relatively little is known about microbial
contamination in hospital lobbies. In the large hospitals included in our study, we found that the lobby
air was contaminated with microorganisms, including bacteria, GNB, and fungi. The levels recorded
(bacteria: 7.2 × 102 CFU/m3; fungi: 5.5 × 102 CFU/m3) were far higher than those hitherto reported in
hospital clean rooms, such as operating rooms, hospital rooms, intensive care units (ICD), surgical
units, hematological wards, pneumonological department and maternity wards [2,5–7]. Levels reported
in hospital rooms with a high degree of cleanliness, such as operating rooms and transplant units, range
from 0.1 to 10 CFU/m3. Augustowska and Dutkiewicz reported that mean monthly microflora
measured in a hospital ward of the pneumonological department in Poland ranged from 257–436
CFU/m3 for airborne bacteria and from 10–96 CFU/m3, respectively [2].